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REPORT.md

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+# Signed Integer Overflow in ExecuTorch Tensor Stride Computation via Unchecked Size Product (.pte)
+
+**Target:** ExecuTorch 1.3.1 (.pte, huntr Model File Vulnerability program)
+**Severity:** Medium (integer overflow with plausible but unproven downstream memory-corruption chain; DoS confirmed)
+**CWE:** CWE-190 (Integer Overflow or Wraparound)
+**Component:** `runtime/core/exec_aten/util/dim_order_util.h` (overflow site) / `runtime/executor/tensor_parser_portable.cpp` (caller)
+**Authentication Required:** No — only requires a victim application to load an attacker-supplied `.pte` file via the standard, always-used `Program::load_method()` API.
+
+## Summary
+
+ExecuTorch computes a tensor's memory strides from its `sizes` and `dim_order` fields during ordinary `.pte` tensor deserialization. The stride computation multiplies a running product of dimension sizes with no overflow check. A `.pte` file with a `Tensor` value whose `sizes` contains a large-but-individually-valid dimension (passing the existing "no negative sizes" check) causes this multiplication to overflow a 32-bit signed integer — Undefined Behavior in C++, caught deterministically by UBSan. This is the first finding across a broader security review of this codebase reached through the core `Method::init()` deserialization path (not a metadata-only accessor), and the first integer-overflow (rather than null-pointer-dereference) bug class identified.
+
+huntr's own Model File Vulnerability program explicitly lists **"integer overflows"** as an example of "vulnerabilities in model file parsing leading to memory corruption" — this finding is a direct, verbatim match for that named category.
+
+## Vulnerability Details
+
+`runtime/executor/tensor_parser_portable.cpp`'s `parseTensor()` validates that no individual size is negative:
+
+```cpp
+for (flatbuffers::uoffset_t i = 0; i < dim; i++) {
+  ET_CHECK_OR_RETURN_ERROR(
+      sizes[i] >= 0,
+      InvalidProgram,
+      "Negative size[%zu] %" PRId32,
+      static_cast<size_t>(i),
+      sizes[i]);
+}
+```
+
+This check does **not** bound the *product* of sizes against the 32-bit signed integer type used for strides. The tensor's strides are subsequently computed via `dim_order_to_stride()` → `dim_order_to_stride_nocheck()` in `runtime/core/exec_aten/util/dim_order_util.h`:
+
+```cpp
+template <typename SizesType, typename DimOrderType, typename StridesType>
+inline void dim_order_to_stride_nocheck(
+    const SizesType* sizes,
+    const DimOrderType* dim_order,
+    const size_t dims,
+    StridesType* strides) {
+  if (dims == 0) return;
+  strides[dim_order[dims - 1]] = 1;
+  for (int32_t i = dims - 2; i >= 0; --i) {
+    if (sizes[dim_order[i + 1]] == 0) {
+      strides[dim_order[i]] = strides[dim_order[i + 1]];
+    } else {
+      strides[dim_order[i]] =
+          strides[dim_order[i + 1]] * sizes[dim_order[i + 1]];   // <-- unchecked multiplication, line 147
+    }
+  }
+}
+```
+
+`StridesType`/`SizesType` default to `int32_t`. This multiplication has **no** overflow check, unlike the analogous computation in `runtime/core/tensor_layout.cpp`'s `calculate_nbytes()` (used by the parallel `.ptd` `TensorLayout` code path), which explicitly calls `c10::mul_overflows()` before trusting the product. The `.pte` `Tensor` stride-computation path has no equivalent protection.
+
+## Steps to Reproduce
+
+### Environment
+Linux x86-64, ExecuTorch 1.3.1 pristine source, clang-16, CMake, Ninja. No authentication, no host access.
+
+### 1. Build ExecuTorch with sanitizers
+
+Same build as REPORT-01 Step 1.
+
+### 2. Build the load_method-level harness (`poc/harness_load_method_fuzzer.cpp`, included in this report)
+
+This is a new harness (not used in prior reports) that goes one layer deeper than metadata-only accessors — it calls `Program::load_method()`, exercising `Method::init()` → `parse_values()` → `parseTensor()`, the CORE tensor-deserialization path used every time a `.pte` is loaded:
+
+```bash
+export ET_PARENT=/path/to/parent-of-executorch
+C10_INC="$ET_SRC/runtime/core/portable_type/c10"
+INCLUDES="-I$ET_PARENT -I$ET_BUILD -I$ET_BUILD/schema/include -I$ET_BUILD/extension/flat_tensor/include -I$ET_BUILD/third-party/flatc_ep/include -I$C10_INC"
+
+clang++-16 -std=c++17 -fsanitize=fuzzer,address,undefined -fno-omit-frame-pointer -fno-sanitize-recover=all \
+  $INCLUDES -DFLATBUFFERS_MAX_ALIGNMENT=1024 -DC10_USING_CUSTOM_GENERATED_MACROS \
+  -c poc/harness_load_method_fuzzer.cpp -o harness.o
+
+clang++-16 -fsanitize=fuzzer,address,undefined -o poc_harness harness.o \
+  "$ET_BUILD/extension/data_loader/libextension_data_loader.a" \
+  "$ET_BUILD/libexecutorch_core.a"
+```
+
+### 3. PoC file
+
+`poc/poc_stride_int_overflow.pte` (24,054 bytes, **included in this report — sha256 `0767af28fc00e63e8ea665beaf5139f7d84332abc435bd8e0de3ebf8d0936e98`**) is a `.pte` file found via coverage-guided fuzzing (within ~10,000 executions) containing a `Tensor` value whose `sizes` array produces a stride-computation overflow. The libFuzzer crash minimizer was unable to reduce this file below its original size while preserving the crash, so the original fuzzer-found file is the canonical reproducer.
+
+### 4. Trigger the crash
+
+```bash
+export ASAN_OPTIONS="abort_on_error=1:symbolize=0"
+export UBSAN_OPTIONS="halt_on_error=1:print_stacktrace=0"
+./poc_harness -timeout=5 -runs=0 poc/poc_stride_int_overflow.pte
+```
+
+### Expected result (secure behavior)
+`Program::load_method()` should return a clean `Error::InvalidProgram` when the size product would overflow the stride computation, matching the overflow-checked pattern already used in `calculate_nbytes()` for the parallel `.ptd` code path.
+
+### Actual result — verified against the pristine, unmodified ExecuTorch 1.3.1 source
+
+```
+Running: poc/poc_stride_int_overflow.pte
+runtime/core/exec_aten/util/dim_order_util.h:147:37: runtime error: signed integer overflow: 8 * 2113929312 cannot be represented in type 'int'
+SUMMARY: UndefinedBehaviorSanitizer: undefined-behavior runtime/core/exec_aten/util/dim_order_util.h:147:37 in
+==<pid>== ERROR: libFuzzer: deadly signal
+    #0 ... (abort machinery)
+    ...
+    dim_order_to_stride_nocheck (dim_order_util.h:147)
+    dim_order_to_stride (dim_order_util.h:168)
+    deserialization::parseTensor (tensor_parser_portable.cpp:144)
+```
+
+Full symbolized call chain (via `addr2line` against the built binary) confirms:
+`dim_order_to_stride_nocheck` (dim_order_util.h:147) ← `dim_order_to_stride` (dim_order_util.h:168) ← `deserialization::parseTensor` (tensor_parser_portable.cpp:144).
+
+**Reproduced 3/3 identical runs against the pristine source** (re-verified live for this report):
+```
+run 1: signed integer overflow: 8 * 2113929312 cannot be represented in type 'int'
+run 2: (identical)
+run 3: (identical)
+```
+
+## Chain Escalation Attempt (Reported Honestly)
+
+Per standard practice of testing whether a confirmed bug can be escalated to a stronger primitive: a second sanitized build was made with **UBSan disabled** (ASan only), so the signed-integer-overflow multiplication would wrap silently instead of aborting — this lets us observe what actually happens to the corrupted stride value downstream, rather than only knowing it aborts under a sanitizer.
+
+**Result: the identical PoC ran cleanly with zero ASan errors** when UBSan wasn't present to trap the overflow. This means:
+
+- The corrupted/wrapped stride value **is** computed and stored in the tensor's `strides` array.
+- **Nothing within `Program::load_method()`'s own code path** (`parse_values`/`parseTensor`/`dim_order_to_stride`) subsequently dereferences or uses that stride to compute a memory address.
+- The stride is only actually *used* for address computation when an **operator executes** and indexes into the tensor's data using it — a step that happens during `Method::execute()`, not `load_method()`.
+
+**This report does not claim a proven memory-corruption chain.** Proving one would require a substantially larger harness — kernel registration via `register_kernels()`, a full `Method::execute()` invocation, and a `.pte` whose instruction chain actually invokes an operator against the malformed tensor — none of which was built in this investigation. The finding is reported as a **confirmed integer-overflow DoS** (deterministic crash under sanitizers; silent, unobserved UB in production builds) with a **plausible but unproven** downstream out-of-bounds access risk during subsequent operator execution.
+
+## Impact
+
+**Who is affected:** Any application calling `Program::load_method()` — the standard, always-used method-loading API — on a `.pte` containing a `Tensor` value with a crafted `sizes` array. This is the core deserialization path, not a rarely-exercised accessor.
+
+**What the attacker can do (proven):** Cause a reliable, deterministic crash (SIGABRT under UBSan) purely by supplying a malformed model file.
+
+**What the attacker might additionally be able to do (unproven, flagged honestly):** If the corrupted/wrapped stride value later feeds into address computation during operator execution, it could plausibly cause an out-of-bounds memory read or write — this was investigated but not demonstrated in this session; see Chain Escalation Attempt above.
+
+**What's at risk:** Availability, confirmed. Integrity/memory-safety during operator execution, plausible but not demonstrated.
+
+**Why Medium, not Critical:** Matches huntr's explicitly-named "integer overflow" example under the memory-corruption category, but only the DoS consequence was proven — claiming a full memory-corruption chain without a working PoC would be overclaiming.
+
+## Suggested Remediation
+
+```cpp
+template <typename SizesType, typename DimOrderType, typename StridesType>
+inline Error dim_order_to_stride_nocheck_safe(
+    const SizesType* sizes,
+    const DimOrderType* dim_order,
+    const size_t dims,
+    StridesType* strides) {
+  if (dims == 0) return Error::Ok;
+  strides[dim_order[dims - 1]] = 1;
+  for (int32_t i = dims - 2; i >= 0; --i) {
+    if (sizes[dim_order[i + 1]] == 0) {
+      strides[dim_order[i]] = strides[dim_order[i + 1]];
+    } else {
+      StridesType product;
+      if (c10::mul_overflows(strides[dim_order[i + 1]], sizes[dim_order[i + 1]], &product)) {
+        return Error::InvalidArgument;
+      }
+      strides[dim_order[i]] = product;
+    }
+  }
+  return Error::Ok;
+}
+```
+
+This mirrors the overflow-checked pattern already correctly implemented in `runtime/core/tensor_layout.cpp`'s `calculate_nbytes()` via `c10::mul_overflows()`.
+
+A regression test should build a `.pte` `Tensor` value whose `sizes` product overflows `INT32_MAX` while each individual size passes the existing non-negative check, asserting `parseTensor()` returns a clean `Error` rather than triggering UB.
+
+## Files Included in This Report
+
+- `poc/poc_stride_int_overflow.pte` — the 24,054-byte PoC file (sha256 `0767af28fc00e63e8ea665beaf5139f7d84332abc435bd8e0de3ebf8d0936e98`)
+- `poc/harness_load_method_fuzzer.cpp` — the harness used to trigger and reproduce the crash, calling `Program::load_method()` directly
+
+## huntr Submission Note
+
+Per the huntr MFV program's submission requirements, this PoC needs to be uploaded to a public HuggingFace repository before filing. `poc/poc_stride_int_overflow.pte` is ready for that upload.

poc/harness_load_method_fuzzer.cpp

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+// libFuzzer harness for Program::load_method() -> Method::init()
+// Targets the ExecutionPlan.delegates iteration in Method::init() specifically -
+// this loop runs BEFORE any kernel/backend resolution, so no kernel or backend
+// registration is required to reach it.
+#include <cstddef>
+#include <cstdint>
+#include <memory>
+#include <vector>
+
+#include <executorch/extension/data_loader/buffer_data_loader.h>
+#include <executorch/runtime/executor/method.h>
+#include <executorch/runtime/executor/program.h>
+#include <executorch/runtime/core/memory_allocator.h>
+#include <executorch/runtime/core/hierarchical_allocator.h>
+#include <executorch/runtime/executor/memory_manager.h>
+#include <executorch/runtime/platform/runtime.h>
+
+using executorch::extension::BufferDataLoader;
+using executorch::runtime::Program;
+using executorch::runtime::Method;
+using executorch::runtime::MemoryAllocator;
+using executorch::runtime::HierarchicalAllocator;
+using executorch::runtime::MemoryManager;
+using executorch::runtime::Span;
+
+static bool g_initialized = false;
+
+extern "C" int LLVMFuzzerTestOneInput(const std::uint8_t* data, std::size_t size) {
+  if (!g_initialized) {
+    executorch::runtime::runtime_init();
+    g_initialized = true;
+  }
+
+  constexpr std::size_t kMaxInput = 8U * 1024U * 1024U;
+  if (data == nullptr || size == 0 || size > kMaxInput) {
+    return 0;
+  }
+
+  BufferDataLoader loader(data, size);
+  auto program = Program::load(&loader, Program::Verification::InternalConsistency);
+  if (!program.ok()) {
+    return 0;
+  }
+
+  // Minimal allocators - large enough for a tiny ExecutionPlan with no real
+  // tensors/kernels; we only need to reach Method::init()'s delegates loop.
+  static std::vector<uint8_t> method_pool(256 * 1024);
+  static std::vector<uint8_t> planned_pool(64 * 1024);
+  MemoryAllocator method_allocator(method_pool.size(), method_pool.data());
+  static Span<uint8_t> planned_span(planned_pool.data(), planned_pool.size());
+  HierarchicalAllocator planned_memory({&planned_span, 1});
+  MemoryManager mm(&method_allocator, &planned_memory, nullptr);
+
+  auto& p = program.get();
+  auto n = p.num_methods();
+  for (size_t i = 0; i < n; ++i) {
+    auto name = p.get_method_name(i);
+    if (name.ok()) {
+      // load_method() calls Method::init() internally. We expect this to
+      // fail gracefully for most fuzzer inputs (missing kernels, etc) -
+      // we're specifically hunting for a crash, not a successful load.
+      auto method = p.load_method(name.get(), &mm);
+      (void)method;
+    }
+  }
+  return 0;
+}